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Decomposing Federal Funds Rate forecast uncertainty using real-time data

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  • Mandler, Martin

Abstract

This paper uses real-time data for the U.S. to estimate out-of-sample forecast uncertainty about the Federal Funds Rate. By combining a Taylor rule with an unobserved components model of economic fundamentals I separate forecast uncertainty into economically interpretable components that represent uncertainty about future economic conditions and uncertainty about future monetary policy. The estimation results indicate important time variation in uncertainty about the future Federal Funds Rate.

Suggested Citation

  • Mandler, Martin, 2007. "Decomposing Federal Funds Rate forecast uncertainty using real-time data," MPRA Paper 13498, University Library of Munich, Germany, revised Jan 2009.
    • Handle: RePEc:pra:mprapa:13498
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    2. Pierdzioch, Christian & Rülke, Jan-Christoph, 2014. "Central banks’ interest rate projections and forecast coordination," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 130-137.

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    More about this item

    Keywords

    monetary policy reaction function; interest rate uncertainty; state-space model;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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